QuantaTravel

• 

  Home Screen

• 

  Quantum Optimized Routes

Inspiration

I was inspired by the complaints of my family and friends. It occurred to me one day that most people want more than one route to travel. It's a psychological fact that humans like having choices to pick from. Stuff like Google Maps or Waze don't really have too good of choices. I also found out that there are many side roads or less major roads that only people who are familiar with the place know. Google Maps doesn't really pick up on these things efficiently. This is why I created QuantaTravel.

What it does

QuantaTravel uses quantum computing to find out the best routes to travel by car. It uses traffic data from NYC for the month of June to train the model, and it gives routes based on that data. It gives three options: a classical route, a quantum time route, and a quantum distance route. The classical route is what google maps would recommend. The quantum time route focuses on optimizing the time and doesn't worry about the distance. It uses the traffic data to optimize this. Quantum distance is kind of like the opposite, where it optimizes distance, and doesn't worry about how much time, because going through traffic is usually the way to get from Point A to B with low distance.

How we built it

I built it using Python completely for the backend. It uses flask for the web service, but unfortunately, the data files have too much data and it takes up too much memory to actually host the website on any free web service. I used pennylane for the quantum computing.

Challenges we ran into

The biggest challenge I ran into for QuantaTravel was getting the quantum routes to follow actual roads. Especially for quantum distance, where it just cut through houses to get the least distance. I eventually fixed it by using OpenStreetMap for road data and incorporating it into the code. Another challenge that I faced was trying to host this as a web app on a free platform. Sadly, the data files I had were too large for any free web service to handle, so this challenge ended up not being solved. 😭

Accomplishments that we're proud of

The biggest accomplishment I'm proud of is how fast the optimization actually works. Throughout coding QuantaTravel, the biggest thing I was worried about was that it was going to take like 5 minutes to finish the quantum computing and show the result. But this, however, was not the case, as I got it to do all the quantum computing in less than 45 seconds every time.

What we learned

Honestly, the most important thing I learned in this was how to do quantum computing. Coming into this hackathon, I knew close to nothing. I follow tons of tutorials and eventually I was able to get the hang of it. So, at the end, I'd say quantum computing is the best thing I learned from making QuantaTravel.

What's next for QuantaTravel

I'd like to host this on a web service and actually make it so that everyone can use it. It's a very good piece of tech, and I'm sure that everyone would benefit from it. Also, another important thing I'd like to add is real time traffic data. I didn't do it for this hackathon because getting the data is not free, but that would definitely be something that could QuantaTravel to the next level.

Built With

• css
• flask
• html
• javascript
• pennylane
• python